Vehicle-mounted self-balancing control method and system

Abstract

The invention relates to the technical field of vehicle-mounted balance control, particularly provides a vehicle-mounted self-balance control method and system, and solves the problems that the application environment of an endoscopic examination bed is limited, and self-balance control cannot be realized according to the use environment. The method comprises the following steps: arranging a gyroscope and a sensor at key parts of an endoscopic examination bed; after receiving the data of the gyroscope and the sensor, the controller performs fusion processing on the data through a fusion control algorithm, distinguishes the real posture change of the bed body of the endoscopic examination bed from the external environment data, and calculates the angle and amplitude of the bed body needing to be adjusted; and according to the calculated angle and amplitude adjustment instruction, an electric push rod or a hydraulic oil cylinder of the execution component executes actions to adjust the posture of the bed body. The system comprises a data acquisition module, a data calculation module and an adjustment execution module. According to the invention, real-time monitoring, accurate calculation and rapid adjustment of the posture of the bed body can be realized in a complex environment (such as vehicle driving), and the stability and accuracy of endoscope operation are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle-mounted balance control, and in particular to a vehicle-mounted self-balancing control method and system. Background Art

[0002] Traditional endoscopy beds typically rely on a stable ground environment and are unable to withstand external disturbances such as vibration and bumps, limiting their application in emergency rescue or mobile medical scenarios. Therefore, developing a vehicle-mounted self-balancing endoscopy system that can maintain stable operation in dynamic environments is of great practical significance.

[0003] Prior art one, Chinese patent, application number: 202111269428.2 discloses an endoscopic examination bed for assisting in changing body positions, which includes a bed body, an examination platform is provided on the upper part of the bed body, and the examination platform includes a movable part and a fixed part; the movable part includes a flipping device and a mobile platform for changing body positions; the mobile platform and the flipping device are slidably connected; the flipping device includes a first flipping assembly and a second flipping assembly; the first flipping assembly and the second flipping assembly have the same structure, and the rotation center lines of the first flipping assembly and the second flipping assembly are parallel and adjacent; when changing body positions, the mobile platform only covers one of the first flipping assembly and the second flipping assembly. Although the endoscopic examination bed assists patients who cannot change their body positions independently to change their body positions through the cooperation of the flipping device and the mobile platform, thereby improving the work efficiency of medical staff; however, its structure is relatively simple, lacks intelligent control, and cannot achieve self-balancing control.

[0004] Prior art 2, Chinese patent application number 202210938045.8, discloses an endoscopic examination bed for assisting in body position change, comprising a bed frame and a support frame for supporting the bed frame, a translation assembly for supporting the patient's waist and hips and capable of lateral movement on the bed frame, and a flip assembly. When the translation assembly drives the patient to move, the flip assembly lifts the patient and assists in flipping. The top of the bed frame is provided with a slot and is divided into three parts by two crossbeams. The translation assembly includes a first plate mounted in the middle slot and capable of lateral reciprocating movement. A guide rod is fixed in the slot and passes through the first plate, and the guide rod is slidably connected to the penetration of the first plate. Although the coordination between the structures allows the patient to be lifted up when the patient needs to change position, thereby assisting the patient to change from a supine position to a side-lying position, thereby achieving the effect of assisting in patient position change, reducing the workload of medical staff and improving examination efficiency, the lack of a self-balancing control function makes the intelligent device suitable for ground applications and cannot be used in environments such as vehicles.

[0005] Prior art three, Chinese patent application number 202410415251.X discloses an endoscopic examination bed for assisting in changing body positions, comprising a fixed base, the lower end of which is fixed on a plane to provide support for the entire device; a rotating portion is fixedly provided on the upper portion of the fixed base; the rotating portion comprises a protective shell, the lower end of which is fixedly connected to the upper end of the fixed base, and the protective shell is provided with a plurality of support seats, both ends of which are rotatably provided with a plurality of support wheels, the outer edges of which are rotatably contacted with support columns, two of which are provided and cooperate with the two ends of the support base to support the lower ends of the support columns; the rotating portion also comprises a limit frame, which is fixedly connected to the interior of the protective shell. Although the angle of the support cushion can be controlled by lifting the support column to change the patient's body position angle, thereby assisting the patient in changing from a supine position to a side-lying position, thereby achieving the effect of assisting in changing the patient's body position, the lack of an autonomous balance adjustment function means that the intelligence level of the device needs to be further improved.

[0006] Currently, the existing technologies 1, 2 and 3 have limited application environments and cannot realize self-balancing control according to the use environment. Therefore, the present invention provides a vehicle-mounted self-balancing control method and system. Summary of the Invention

[0007] In order to achieve the above object, the present invention adopts the following technical solutions: One aspect of the present invention provides a vehicle-mounted self-balancing control method, comprising the following steps: Gyroscopes and sensors are placed at key locations on the endoscopic examination table. The gyroscopes are used to capture the table's tilt and rotation data, while the sensors are used to capture the table's vibration and external environmental data, including bumps and vibrations during travel. After receiving data from the gyroscope and sensors, the controller fuses the data through a fusion control algorithm, distinguishes the actual posture changes of the endoscope bed from the external environment data, and calculates the angle and amplitude of the bed that needs to be adjusted; According to the adjustment instructions corresponding to the calculated angle and amplitude, the electric push rod or hydraulic cylinder of the executive component performs the action to adjust the bed posture; if the executive component fails, it automatically switches to the backup component or mode.

[0008] In an optional embodiment, the process of deploying gyroscopes and sensors at key locations on an endoscopic examination bed includes the following steps: Conduct mechanical analysis on key parts of the bed to determine which areas are affected by the external environment and which areas are sensitive to adjustments to the bed's posture. Key parts include the bed's center of gravity, the connection points of the support frame, and the contact surfaces of the moving devices. The gyroscope is aligned with the rotation axis of the bed, and the sensor is placed in an area that is subject to interference from the external environment; After the deployment is complete, the gyroscope and sensors are connected to the controller and initialized.

[0009] In an optional embodiment, the calculation formula for the force distribution of the bed during mechanical analysis and key position positioning is: ; Where, It represents the total force on the bed; Indicates the The elastic potential energy of key parts; Indicates the coordinates of the bed in three-dimensional space; Indicates the slight displacement of the bed in three directions; Indicates the The torque of the external environment on the bed; Indicates the The rotation angle under the action of torque; Indicates the number of key parts; Indicates the amount of external environmental interference; Key parts sensitivity assessment formula: ; Where, Indicates the Sensitivity index of key parts; Indicates the The position vector of each key part; Indicates the The posture vectors of key parts; Represents a time variable.

[0010] In an optional implementation, the gyroscope alignment error calculation formula in the precise placement of the gyroscope and the sensor is: ; Where, represents the gyroscope alignment error; Indicates the actual rotation angular velocity measured by the gyroscope; Indicates the angular velocity of the gyroscope under ideal alignment; Sensor placement optimization function: ; Where, represents the optimization objective function of sensor placement, Indicates the The data collection accuracy of each sensor; Indicates the The vibration intensity of the external environment interference; Represents the weight coefficient of the three-dimensional coordinates of space; represents the weight coefficient of the time variable; Indicates the number of sensors; Indicates the amount of external environmental interference.

[0011] In an optional embodiment, the sensor is connected to the controller, and the adjustment of the initialization error includes: ; Where, Indicates the data acquisition system initialization error; Indicates the Calibration parameters of each sensor; Indicates the The response parameters of each controller; Indicates a time interval; Indicates the frequency interval; Indicates the number of sensors; Indicates the number of controllers; Data transmission delay compensation: ; Where, Indicates the data transmission delay compensation time; Indicates the Transmission delay of each data link; Indicates the Processing delay of each controller; Indicates small changes in data transmission distance; Indicates small changes in the controller's processing power; Indicates the number of data links; Indicates the number of controllers.

[0012] In an optional embodiment, the process of calculating the angle and amplitude of the bed that needs to be adjusted includes the following steps: Get multi-dimensional data from gyroscopes and sensors; The controller uses dynamic weighting to compare and correct the bed tilt and rotation data captured by the gyroscope with the vibration and external environment data captured by the sensor, organically integrating data from different sources and distinguishing the actual posture changes of the endoscopy bed from the external environment data. The controller calculates the angle and amplitude of the bed that needs to be adjusted based on the organically integrated data; the controller dynamically generates adjustment instructions based on the difference between the current posture of the bed and the target posture, and the adjustment instructions include the current state of the bed.

[0013] In an optional embodiment, the process of distinguishing the actual posture change of the endoscopic examination bed from the external environment data includes the following steps: The controller first obtains multi-dimensional data from the gyroscope and sensors, including bed tilt, rotation, vibration, and external environmental data. It then organically fuses the gyroscope and sensor data using a dynamic weighting formula, using a Gaussian function to eliminate noise and outliers to generate preliminary fused data. Based on the fused data, the controller uses the environmental impact separation formula to eliminate the influence of external environmental data on the bed posture; and uses the change rate of external environmental data and the normalization function to calculate the true posture data; The controller calculates the noise correction factor through the environmental noise correction formula, and performs final correction on the real posture data to generate the bed posture data.

[0014] In an optional implementation, the process of dynamically generating an adjustment instruction includes the following steps: Perform dynamic calculation based on the difference between the current posture of the bed and the target posture; The controller simulates the movement trajectory of the bed under different adjustment ranges and predicts the adjustment angle and range based on the changing trend of the external environment; Dynamically generate a comprehensive instruction that includes the current state and predicted impact, including the specific angle and amplitude of the bed that needs to be adjusted, as well as a compensation strategy for external environmental interference. If vibration interference is detected in the external environment, the corresponding compensation value is added to the adjustment instruction.

[0015] In an optional embodiment, the process of executing an action by an electric push rod or a hydraulic cylinder of an actuator includes the following steps: The adjustment instructions are transmitted to the electric push rod or hydraulic cylinder. The electric push rod is driven by a precise motor to push or pull the specific part of the bed, while the hydraulic cylinder realizes the smooth adjustment of the bed through the pressure change of the hydraulic system. During the adjustment process, the gyroscope and sensors continuously monitor the changes in the bed's posture and feed back real-time data to the controller; the controller dynamically corrects the adjustment instructions based on the feedback data; If the actuator fails, it automatically switches to the backup component or mode; when the electric push rod fails, the hydraulic cylinder will immediately take over the adjustment task.

[0016] Another aspect of the present invention provides a vehicle-mounted self-balancing control system, comprising: The data acquisition module is configured to deploy gyroscopes and sensors at key locations on the endoscopic examination table. The gyroscope is used to capture the table's tilt and rotation data, and the sensors are used to capture the table's vibration and external environment data, including data on bumps and vibrations during travel. The data calculation module is configured as a controller that receives data from the gyroscope and sensors, fuses the data through a fusion control algorithm, distinguishes the actual posture changes of the endoscope bed from the external environment data, and calculates the angle and amplitude of the bed that needs to be adjusted; The adjustment execution module is configured to execute actions according to the adjustment instructions corresponding to the calculated angle and amplitude through the electric push rod or hydraulic cylinder of the execution component to adjust the bed posture; if the execution component fails, it automatically switches to the backup component or mode.

[0017] Based on the above solution, the present invention has at least the following technical effects: The data acquisition and monitoring system of this invention uses gyroscopes and sensors to capture real-time changes in the endoscopic examination table's posture (such as tilt and rotation) and external environmental disturbances (such as bumps and vibrations during driving). The gyroscope primarily monitors the table's angle and rotation, while the sensors capture vibration and external environmental data, forming a comprehensive data foundation. Data fusion and noise filtering utilizes a fusion control algorithm to comprehensively analyze the gyroscope and sensor data, distinguishing between the table's true posture changes and external environmental disturbances. Irrelevant vibration and noise signals from the external environment are filtered out, retaining the table's true posture data. Based on this fused data, the angle and amplitude of required bed adjustments can be accurately calculated. Posture adjustment and fault tolerance utilize actuators such as electric push rods or hydraulic cylinders to quickly and accurately adjust the table's posture, ensuring stable endoscopic operation. If an actuator fails, the system automatically switches to a backup component or mode, ensuring continuous and reliable operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 This is a flow chart of the vehicle-mounted self-balancing control method provided in Example 1 of the present invention; Figure 2 This is a diagram of the process of deploying gyroscopes and sensors at key locations on an endoscopic examination bed, as provided in Example 2 of the present invention; Figure 3 This is a diagram of the process of calculating the angle and amplitude that the bed needs to be adjusted, provided in Example 3 of the present invention; Figure 4 A diagram illustrating the process of distinguishing between the actual posture change of the endoscopic examination bed and external environment data provided in Example 4 of the present invention; Figure 5 This is a process diagram of dynamically generating adjustment instructions provided in Example 5 of the present invention; Figure 6This is a diagram of a process of executing an action by an electric push rod or a hydraulic cylinder of an actuator provided in Example 6 of the present invention; Figure 7 This is a block diagram of the vehicle-mounted self-balancing control system provided in Example 7 of the present invention; Figure 8 A block diagram of the electronic device provided by the present invention; Figure 9 Block diagram of the computer-readable storage medium provided by the present invention. DETAILED DESCRIPTION

[0019] The technical solutions in the embodiments of the present invention will be described below with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0020] In the following, the terms "first," "second," etc., are used for descriptive convenience only and should not be construed as indicating or implying relative importance or implicitly specifying the number of the technical features being referred to. Thus, a feature identified with "first," "second," etc., may explicitly or implicitly include one or more of such features. In the description of the present invention, unless otherwise specified, "plurality" means two or more.

[0021] In the present invention, unless otherwise clearly specified and limited, the term "connection" should be understood in a broad sense. For example, "connection" can be a fixed mechanical connection, a detachable mechanical connection, or an integrated one; or, "connection" can be a direct connection or an indirect connection through an intermediate medium. In addition, unless otherwise clearly specified and limited, the term "coupling" should be understood in a broad sense. For example, "coupling" can be a direct electrical connection, such as physical contact and electrical conduction between two components, or it can be understood as the electrical connection between different components in a circuit structure through a physical line that can transmit electrical signals, such as printed circuit board (PCB) copper foil or wire, so as to transmit electrical signals; or, "coupling" can be an indirect electrical connection between two components through an intermediate medium; or, "coupling" can be an electrical connection between two components in an airless / non-contact manner, such as electrical connection between two components using capacitive coupling to transmit electrical signals.

[0022] In an embodiment of the present invention, directional terms such as "up", "down", "left" and "right" may be defined including but not limited to the orientation relative to the schematic placement of the components in the drawings. It should be understood that these directional terms may be relative concepts, which are used for relative description and clarification, and may change accordingly according to changes in the orientation of the components in the drawings.

[0023] Example 1: like Figure 1 As shown, an embodiment of the present invention provides a vehicle-mounted self-balancing control method, comprising the following steps: Step S100: gyroscopes and sensors are placed at key locations of the endoscopic examination bed. The gyroscopes are used to capture tilt and rotation data of the endoscopic examination bed, and the sensors are used to capture vibration data and external environmental data of the endoscopic examination bed, including bumps and vibration data during driving. Step S200: After receiving the data from the gyroscope and the sensor, the controller fuses the data using a fusion control algorithm, distinguishes the actual posture change of the endoscope bed from the external environment data, and calculates the angle and amplitude of the bed that needs to be adjusted; Step S300: According to the adjustment instructions corresponding to the calculated angle and amplitude, the electric push rod or hydraulic cylinder of the execution component performs the action to adjust the bed posture; if the execution component fails, it automatically switches to the backup component or mode.

[0024] In the above embodiment, step S100 involves data acquisition and monitoring. Using gyroscopes and sensors, the system can capture real-time changes in the endoscopic examination table's posture (e.g., tilt and rotation) and external environmental disturbances (e.g., bumps and vibrations during vehicle travel). The gyroscope primarily monitors the table's angle and rotation, while the sensors capture vibration and external environmental data, forming a comprehensive data foundation. This provides high-precision, real-time data support for posture adjustment, ensuring rapid response to the table's posture changes and external disturbances, laying the foundation for stable operation. Step S200 involves data fusion and noise filtering. A fusion control algorithm comprehensively analyzes the gyroscope and sensor data to distinguish between the table's true posture changes and external environmental disturbances. It filters out irrelevant vibration and noise signals from the external environment, retaining the table's true posture data. Based on this fused data, the angle and amplitude of the required adjustment can be accurately calculated. This improves anti-interference capabilities, ensuring accurate identification of the table's true posture even in complex environments (e.g., during vehicle travel). This provides an accurate calculation basis for posture adjustment, avoiding misjudgments and erroneous operations caused by external disturbances. Step S300, posture adjustment and fault tolerance, uses actuators such as electric push rods or hydraulic cylinders to quickly and accurately adjust the bed's posture, ensuring the stability of endoscopic operation. If an actuator fails, it automatically switches to a backup component or mode, ensuring continuous and reliable operation. This ensures the stability of the endoscopic bed during earthquakes, wartime, or when a vehicle is moving, providing reliable support for medical rescue operations. It also improves the system's robustness and fault tolerance, reducing the risk of operational interruptions due to equipment failure.

[0025] In summary, this embodiment enables real-time monitoring, precise calculation, and rapid adjustment of the bed posture in complex environments (such as while a vehicle is moving), thereby ensuring the stability and accuracy of endoscopic operation. Through data fusion and noise filtering, it can effectively cope with external environmental interference and avoid misoperation. The fault-tolerant mechanism ensures that the system can still operate normally when some components fail, thereby improving the reliability and practicality of the equipment. It provides technical support for the stable operation of on-board medical equipment (especially endoscopic examination systems) during earthquakes, wartime, or when the vehicle is moving, and has important practical application value.

[0026] Example 2: like Figure 2 As shown, based on Example 1, the process of deploying gyroscopes and sensors at key positions of the endoscopic examination bed in step S100 provided in this embodiment of the present invention includes the following steps: Step S101: Perform a mechanical analysis on key parts of the bed to determine which areas are affected by the external environment (such as vehicle bumps and vibrations) and which areas are sensitive to adjustments to the bed's posture. Key parts include the bed's center of gravity, the connection points of the support frame, and the contact surfaces of the moving device. Step S102: The gyroscope is aligned with the rotation axis of the bed, and the sensors are placed in areas subject to external environmental interference; for example, the acceleration sensor is used to capture vibration data, and the pressure sensor is used to detect the interaction force between the bed and the support frame; Step S103: After the deployment is completed, the gyroscope and the sensor are connected to the controller and initialized.

[0027] The calculation formula for the force distribution of the bed in step S101 mechanical analysis and key position positioning is: ; Where, It represents the total force on the bed; Indicates the The elastic potential energy of key parts; Indicates the coordinates of the bed in three-dimensional space; Indicates the slight displacement of the bed in three directions; Indicates the The torque of the bed caused by the external environment (such as bumps and vibrations); Indicates the The rotation angle under the action of torque; Indicates the number of key parts; Indicates the amount of external environmental interference; Key parts sensitivity assessment formula: ; Where, Indicates the Sensitivity index of key parts; Indicates the The position vector of each key part; Indicates the The posture vectors of key parts; Represents a time variable.

[0028] Step S102: Calculation formula for gyroscope alignment error in precise placement of gyroscope and sensor: ; Where, represents the gyroscope alignment error; Indicates the actual rotation angular velocity measured by the gyroscope; Indicates the angular velocity of the gyroscope under ideal alignment; Sensor placement optimization function: ; Where, represents the optimization objective function of sensor placement, Indicates the The data collection accuracy of each sensor; Indicates the The vibration intensity of the external environment interference; Represents the weight coefficient of the three-dimensional coordinates of space; represents the weight coefficient of the time variable; Indicates the number of sensors; Indicates the amount of external environmental interference.

[0029] In step S103, the sensor is connected to the controller, and the adjustment of the initialization error includes: ; Where, Indicates the data acquisition system initialization error; Indicates the Calibration parameters of each sensor; Indicates the The response parameters of each controller; Indicates a time interval; Indicates the frequency interval; Indicates the number of sensors; Indicates the number of controllers; Data transmission delay compensation: ; Where, Indicates the data transmission delay compensation time; Indicates the Transmission delay of each data link; Indicates the Processing delay of each controller; Indicates small changes in data transmission distance; Indicates small changes in the controller's processing power; Indicates the number of data links; Represents the number of controllers. This ensures the scientific, precise, and efficient placement of gyroscopes and sensors in key locations on the endoscopic examination bed. Each formula combines the core requirements of mechanical analysis, data acquisition, and system control, providing a solid theoretical foundation and technical support for the bed's self-balancing control.

[0030] In the above-mentioned embodiment, step S101, mechanical analysis and key location positioning, involves mechanical analysis of key bed components. This allows for precise identification of areas of the bed most susceptible to environmental impacts (such as bumps and vibrations) during vehicle operation, as well as those most sensitive to bed posture adjustments. This analysis not only considers the bed's static structural characteristics but also incorporates the dynamic operating environment, ensuring a targeted and efficient deployment plan. Significance: This provides a scientific basis for gyroscope and sensor deployment. Mechanical analysis can avoid resource waste or inaccurate data collection caused by blind deployment, while also laying the data foundation for the bed's self-balancing control. Furthermore, it demonstrates a deep understanding of the bed's structure, ensuring the innovation and practicality of the deployment plan. Step S102: The precise placement of the gyroscopes and sensors. The alignment of the gyroscopes with the bed's rotation axis ensures accurate capture of posture data, while the sensor placement covers key areas of the bed exposed to external environmental interference. The acceleration sensor can capture vibration data in real time, while the pressure sensor can detect the interaction force between the bed and the support frame. This placement not only improves the comprehensiveness of data acquisition but also enhances the system's anti-interference capabilities. Significance: It provides high-quality data input for the controller. The precise placement of the gyroscopes ensures real-time monitoring of bed posture changes, while the rational distribution of the sensors fully reflects the impact of the external environment on the bed. The comprehensiveness and accuracy of data acquisition provide a reliable foundation for the control algorithm, thereby improving the accuracy and stability of the bed's self-balancing control. Step S103: The data acquisition system is connected to the controller and initialized. After the placement is complete, the gyroscopes and sensors are connected to the controller via the high-precision data acquisition system and initialized. This ensures real-time data acquisition and a high sampling rate. Initialization also calibrates the system, reducing errors in data transmission. Significance: This achieves seamless integration between the data acquisition system and the controller, providing an efficient data transmission channel for the integrated control algorithm. The initialization operation further improves the reliability and stability of the system, ensuring the real-time and accuracy of the bed's self-balancing control.

[0031] In summary, the placement of the gyroscopes and sensors in this embodiment not only accurately captures changes in the bed's posture and external environmental interference, but also provides a high-quality data foundation for the bed's self-balancing control. This not only demonstrates a deep understanding of the bed's structure but also reliably ensures the stable operation of the endoscopic examination bed while in motion, thereby improving examination accuracy and patient safety.

[0032] Example 3: like Figure 3 As shown, based on Example 1, the process of calculating the angle and amplitude of the bed that needs to be adjusted in step S200 provided in this embodiment of the present invention includes the following steps: Step S201: Acquire multi-dimensional data from the gyroscope and sensor; Step S202: The controller compares and corrects the bed tilt and rotation data captured by the gyroscope with the vibration and external environment data captured by the sensor through dynamic weighting, organically integrating the data from different sources and distinguishing the actual posture changes of the endoscopy bed from the external environment data; Step S203: The controller calculates the angle and amplitude of the bed that needs to be adjusted based on the organically integrated data; the controller dynamically generates adjustment instructions based on the difference between the current posture of the bed and the target posture. The adjustment instructions include the current state of the bed and also predict the impact of the external environment.

[0033] In the above embodiment, step S201 obtains multi-dimensional data from the gyroscope and sensor, and uses the gyroscope and sensor to capture the tilt and rotation data of the bed and the vibration and bump data of the external environment, respectively, to form multi-dimensional data. These data provide basic information for subsequent analysis and adjustment. Significance: Multi-dimensional data ensures that the posture changes of the bed and the influence of the external environment can be fully perceived, avoiding the limitations that may be brought about by a single data source; comprehensive data collection lays a solid foundation for subsequent precise adjustments. The controller in step S202 compares and corrects the data from the gyroscope and sensor through dynamic weighting, distinguishing between the posture changes of the bed itself and the interference caused by the external environment. The organic fusion not only improves the accuracy of the data, but also enhances the system's adaptability to the external environment. Significance: Dynamic weighting and organic fusion enable the system to accurately identify the true posture changes of the bed in complex environments, avoiding the misleading of the adjustment process by external interference; improving the robustness and reliability of the system, and ensuring that the bed can remain stable in various environments. Based on the fused data, the controller in step S203 uses an adaptive algorithm to calculate the required bed adjustment angle and amplitude, and dynamically generates adjustment instructions. This not only takes into account the bed's current state but also anticipates potential environmental influences, ensuring smooth and precise adjustments. Significance: This system achieves precise control of the bed's posture, making the adjustment process more intelligent and efficient. By anticipating environmental influences, the system can proactively address potential interference during the adjustment process, further improving the system's stability and adaptability. This system enables the bed to consistently maintain its optimal posture in dynamic environments, meeting the demands of high-precision applications.

[0034] In summary, this embodiment achieves high-precision adjustment of the bed's posture. It can accurately identify the bed's actual posture changes in complex environments and dynamically generate adjustment instructions to ensure the bed remains stable. This not only improves the system's accuracy and stability, but also enhances its adaptability to external environments, allowing the bed to maintain its optimal posture under various complex conditions.

[0035] Example 4: like Figure 4 As shown, based on Example 3, the process of distinguishing the actual posture change of the endoscopic examination bed from the external environment data in step S202 provided in this embodiment of the present invention includes the following steps: Step S2021: The controller first obtains multi-dimensional data from the gyroscope and sensors, including bed tilt, rotation, vibration, and external environment data; organically fuses the gyroscope and sensor data through a dynamic weighting formula, and uses a Gaussian function to eliminate noise and outliers to generate preliminary fused data; Step S2022: Based on the fused data, the controller uses an environmental impact separation formula to eliminate the influence of the external environmental data on the bed posture; and calculates the true posture data using the rate of change of the external environmental data and a normalization function; Step S2023: The controller calculates the noise correction factor through the environmental noise correction formula, and performs final correction on the real posture data to generate bed posture data.

[0036] Among them, data dynamic weighted fusion: ; Where, Indicates the fused data, the actual posture change of the bed, Indicates the bed tilt and rotation data captured by the gyroscope; Represents the vibration data captured by the sensor; Represents external environmental data captured by the sensor (such as temperature, air pressure, etc.); Indicates the dynamic weighting coefficient, which is adjusted according to the real-time changes of data; Represents the average value of gyroscope, vibration sensor and external environment data; Represents the standard deviation of gyroscope, vibration sensor and external environment data; represents the Gaussian function, which is used to eliminate noise and outliers; Separation of true posture and external environment data: ; Where, Represents the actual posture changes of the bed, eliminating the influence of the external environment; represents the fused data; Indicates the environmental impact separation coefficient, which is dynamically adjusted according to the complexity of the external environment; Indicates the rate of change of external environment data; Represents a normalization function, which is used to smooth the influence of external environment data; Dynamic weighting coefficient update: ; Where, Indicates the Dynamic weighting coefficients of data sources, ; represents the fused data; Indicates the The mean of the data sources; Indicates the The standard deviation of each data source; Represents a Gaussian function, which is used to dynamically adjust weights; Ambient noise correction: ; Where, represents the environmental noise correction factor; Indicates the External environmental data of each sampling point; Indicates the total number of sampling points; represents the absolute value function, which is used to calculate the noise intensity; Final data correction: ; Where, Indicates the final corrected bed posture data; Represents the real posture data; represents the environmental noise correction factor; Indicates the maximum value of the environmental noise correction factor; accurate processing of bed posture data is achieved through dynamic weighted fusion, true posture separation, weighted coefficient update, environmental noise correction and final data correction.

[0037] In the above embodiment, step S2021 performs data fusion and weighting, using a Gaussian function to eliminate noise and outliers, improving data accuracy and reliability. The purpose of this process is to integrate data from different sources into a unified framework, providing a foundation for processing. By eliminating noise and outliers, the accuracy and stability of the data are ensured, providing high-quality data input for subsequent steps. Step S2022 performs posture separation and correction, using the rate of change of external environmental data and a normalization function to smooth the influence of external environmental data and ensure the accuracy of posture data. The purpose of this process is to eliminate external environmental interference, ensuring the authenticity and accuracy of bed posture changes; improving the system's adaptability to different environmental conditions, ensuring accurate bed posture identification in various complex environments. Step S2023 performs noise correction and output, optimizing the data using a noise correction factor, further improving data accuracy and reliability. The purpose of this process is to further optimize the data through noise correction, ensuring the high accuracy and reliability of the final output bed posture data; improving the stability and robustness of the system, ensuring accurate bed posture data in various complex environments.

[0038] In summary, this embodiment achieves accurate recognition and correction of posture changes of an endoscope bed through data fusion, posture separation, and noise correction.

[0039] Example 5: like Figure 5 As shown, based on Example 3, the process of dynamically generating the adjustment instruction in step S203 provided by the embodiment of the present invention includes the following steps: Step S2031: performing dynamic calculation based on the difference between the current posture of the bed and the target posture; Step S2032: The controller simulates the movement trajectory of the bed under different adjustment ranges and predicts the adjustment angle and range based on the changing trend of the external environment; Step S2033: Dynamically generate a comprehensive instruction that includes the current state and predicted impact, including the specific angle and amplitude of the bed that needs to be adjusted, and also includes a compensation strategy for external environmental interference. If vibration interference is detected in the external environment, the corresponding compensation value is added to the adjustment instruction.

[0040] Among them, step S2031 dynamically calculates the difference between the current posture of the bed and the target posture: ; Where, Indicates the difference between the current posture of the bed and the target posture (angle deviation); Indicates that the bed is The current angle in degrees of freedom; represents the time variable; Indicates that the bed is Static error coefficient on degrees of freedom; Indicates that the bed is Dynamic error coefficient on degrees of freedom; Represents the weight coefficient, which is used to balance the effects of angle deviation and position deviation; Indicates the current position vector of the bed; Represents the position vector of the bed target; Represents the initial position vector of the bed; it takes into account the angular deviation and position deviation of the bed in each degree of freedom, and balances the influence of the two through the weight coefficient, and finally calculates the overall difference between the current posture of the bed and the target posture; Step S2032 simulates the bed's motion trajectory and predicts the adjustment angle and amplitude: ; Where, Indicates the predicted adjustment angle and magnitude; Represents the motion trajectory matrix of the bed; represents the mass matrix of the bed; Represents the force vector of the external environment on the bed; Indicates the initial time; Indicates the final time; Indicates the compensation coefficient of environmental interference; Represents the change vector of the external environment (such as vibration, wind force, etc.); Represents the maximum change vector of the external environment; by integrating the motion trajectory matrix of the bed, combining the external environmental force and the environmental change vector, the adjustment angle and amplitude of the bed are predicted, and the compensation coefficient is used to adjust the impact of environmental interference; Step S2033 generates a comprehensive instruction and adds a compensation strategy: ; Where, represents the generated synthesis instruction; Represents the rotation matrix of the bed; Indicates the predicted adjustment angle and magnitude; Indicates the difference between the current posture and the target posture; represents the gain matrix of the compensation strategy; represents the detected vibration disturbance vector; represents the maximum permissible vibration disturbance vector; represents the compensation value matrix; the predicted adjustment angle and current posture difference are combined to generate comprehensive adjustment instructions. Simultaneously, the external vibration disturbance is dynamically compensated for using the compensation strategy's gain matrix and compensation value matrix. The above formulas precisely describe the process of dynamically generating adjustment instructions. Each formula incorporates the bed's motion state, changes in the external environment, and the compensation strategy to ensure the accuracy and robustness of the adjustment instructions.

[0041] In the above embodiment, step S2031 dynamically calculates the difference between the bed's current posture and the target posture. Through real-time data acquisition and calculation, the difference between the current and target postures is accurately quantified. The difference may include angle deviation, height deviation, or position deviation. This dynamic calculation can quickly identify the specific parameters that need to be adjusted, providing a data basis for generating adjustment instructions. Significance: Ensures the accuracy and real-time nature of adjustments. Dynamic calculation enables rapid response to changes in the bed's state, avoiding adjustment failures or instability due to delays or errors. It also provides reliable data support for simulation and prediction. Step S2032 simulates the bed's motion trajectory and predicts the adjustment angle and amplitude, effectively preventing over- or under-adjustment of the bed during the adjustment process. Significance: Improves the intelligence and adaptability of adjustments. Through simulation and prediction, the bed's motion state can be predicted in advance, thereby generating more reasonable adjustment instructions. This not only improves adjustment efficiency but also reduces the risk of adjustment failure due to changes in the external environment. Step S2033 generates a comprehensive instruction and incorporates a compensation strategy. Factors such as the current state, predicted impact, and external environmental interference are comprehensively considered to generate a comprehensive instruction that includes specific adjustment angles, amplitudes, and compensation strategies. For example, if vibration interference is detected in the external environment, a corresponding compensation value is added to the adjustment instruction to ensure that the bed remains stable during the adjustment process. Significance: This ensures comprehensive and robust adjustments. By incorporating a compensation strategy, the system can effectively cope with interference from the external environment and ensure that the bed can still be accurately adjusted to the target posture in complex environments. This not only improves the reliability of the system, but also enhances the user experience.

[0042] In summary, the entire process of dynamically generating adjustment instructions in this embodiment achieves high-precision, high-efficiency, and strong adaptability in bed adjustment through dynamic calculation, simulation prediction, and comprehensive compensation. This not only improves bed performance but also provides an important technical reference for the future development of smart homes and medical devices.

[0043] Example 6:

[0044] like Figure 6 As shown, based on Example 1, the process of executing an action by the electric push rod or hydraulic cylinder of the actuator in step S300 provided in the embodiment of the present invention includes the following steps: Step S301: The adjustment command is transmitted to the electric push rod or hydraulic cylinder. The electric push rod is driven by a precise motor to push or pull a specific part of the bed, while the hydraulic cylinder achieves smooth adjustment of the bed through pressure changes in the hydraulic system. Step S302: During the adjustment process, the gyroscope and sensor continuously monitor the posture changes of the bed and feed back the real-time data to the controller; the controller dynamically corrects the adjustment instructions based on the feedback data; Step S303: If the execution component fails, it automatically switches to the backup component or mode; when the electric push rod fails, the hydraulic cylinder will immediately take over the adjustment task.

[0045] In the above embodiment, the execution of the adjustment instructions in step S301 ensures that the bed can quickly respond to the controller's instructions and complete posture adjustment. The purpose of this implementation is to convert the controller's computational instructions into actual physical movements. The combination of the electric push rod and the hydraulic cylinder ensures both rapid adjustment (the high response speed of the electric push rod) and smooth adjustment (the stable output of the hydraulic cylinder). The dual-mode design enables the system to adapt to different adjustment requirements, such as rapid correction or fine-tuning. In step S302, dynamic feedback and correction are implemented. The controller dynamically corrects the adjustment instructions based on feedback data to ensure the stability and accuracy of the bed's posture. The purpose of this implementation is to achieve closed-loop control, enabling the system to perceive the bed's actual state in real time and dynamically adjust to changes in the external environment (such as vehicle turbulence). The dynamic feedback mechanism is similar to the human body's balance system, enabling it to maintain stability in complex environments. Real-time corrections can avoid posture deviations caused by external interference or execution errors, ensuring accurate and reliable adjustments. Step S303, fault handling and redundancy design, demonstrates the system's redundancy and fault tolerance capabilities. By automatically switching between backup components or modes, the system can continue to function when a component fails, avoiding paralysis of the entire system due to failure of a single component. This significantly improves the reliability and safety of the system and is particularly suitable for scenarios with extremely high stability requirements, such as medical equipment.

[0046] In summary, this embodiment, through the coordinated operation of electric push rods and hydraulic cylinders, combined with a dynamic feedback and correction mechanism, enables high-precision posture adjustment, ensuring the stability of the bed in various complex environments. The design of dual-mode actuators (electric push rods and hydraulic cylinders) enables the system to adapt to different adjustment requirements, such as rapid response or fine-tuning, while also providing the ability to cope with sudden failures. The redundant design and fault handling mechanism ensure the system's reliability under extreme conditions and reduce the risk of actuator failure, making it particularly suitable for scenarios with high safety requirements, such as medical equipment. The dynamic feedback and correction mechanism gives the system intelligent characteristics, enabling it to autonomously sense environmental changes and make corresponding adjustments, reducing the need for manual intervention and improving the system's automation level. Through the synergistic effect of the above steps, the on-board self-balancing control system not only achieves high-precision adjustment of the bed's posture, but also significantly improves the system's reliability, safety, and intelligence through its redundant design and dynamic feedback mechanism.

[0047] Example 7:

[0048] like Figure 7As shown, based on Examples 1 to 6, the vehicle-mounted self-balancing control system provided by the embodiment of the present invention includes: The data acquisition module 1 is configured to deploy gyroscopes and sensors at key locations of the endoscopic examination bed. The gyroscope is used to capture the inclination and rotation data of the endoscopic examination bed, and the sensors are used to capture the vibration data of the endoscopic examination bed and external environmental data, including data on bumps and vibrations during driving. The data calculation module 2 is configured as a controller that receives data from the gyroscope and sensors, fuses the data through a fusion control algorithm, distinguishes the actual posture changes of the endoscope bed from the external environment data, and calculates the angle and amplitude of the bed that needs to be adjusted; The adjustment execution module 3 is configured to execute actions according to the adjustment instructions corresponding to the calculated angle and amplitude through the electric push rod or hydraulic cylinder of the execution component to adjust the bed posture; if the execution component fails, it automatically switches to the backup component or mode.

[0049] In the above embodiment, the data acquisition module senses the bed's posture changes and external environmental influences in real time. Using high-precision gyroscopes and sensors, it accurately captures the bed's dynamic information, providing reliable data support for data processing and posture adjustment. This enables the system to adapt to complex dynamic environments (such as vehicle bumps) and ensures comprehensive and accurate data acquisition. The data calculation module distinguishes the bed's actual posture changes from external environmental data (such as vehicle bumps), accurately calculating the required angle and magnitude of bed adjustment, and intelligently analyzes and processes the data. Through a fusion control algorithm, the system effectively filters out external interference (such as vehicle bumps) and focuses on the bed's actual posture changes. Intelligent data processing enables the system to generate precise adjustment instructions, ensuring the stability and accuracy of the bed's posture, significantly enhancing the system's intelligence and reducing the need for manual intervention. The adjustment execution module converts the calculation instructions into actual physical actions. The coordinated operation of electric actuators and hydraulic cylinders enables fast and smooth adjustment of the bed's posture. Furthermore, the redundant design and fault handling mechanism enable the system to automatically switch to backup mode in the event of an execution component failure, ensuring the continuity and reliability of adjustment tasks. The system stability and security are significantly improved, and it is particularly suitable for high-demand scenarios such as medical equipment.

[0050] In summary, this embodiment, through the real-time perception of the data acquisition module, the intelligent analysis of the data calculation module, and the precise execution of the adjustment execution module, can achieve high-precision posture adjustment of the endoscopic examination bed, ensuring the stability and safety of medical operations. The fusion control algorithm of the data calculation module gives the system intelligent characteristics, capable of autonomously distinguishing between actual posture changes and external environmental interference and generating precise adjustment instructions; the intelligent design significantly improves the system's automation level and reduces the need for manual intervention; the multi-dimensional data acquisition capabilities of the data acquisition module enable the system to adapt to complex dynamic environments (such as bumps during vehicle driving), ensuring the stability of the bed's posture; the redundant design and fault handling mechanism of the adjustment execution module ensure that the system can continue to operate normally even when the execution component fails, significantly improving the system's reliability and safety. Through the synergistic effect of the above modules, the on-board self-balancing control system not only achieves high-precision posture adjustment of the endoscopic examination bed in dynamic environments, but also significantly improves the system's stability, safety, and automation level through intelligent design and redundant mechanisms.

[0051] Figure 8 A block diagram is shown of an exemplary electronic device that is suitable for implementing embodiments of the present invention.

[0052] The electronic device may include a central processing unit / microprocessor / main control chip, etc. 4; a storage medium 5, coupled to the central processing unit / microprocessor / main control chip, etc. 4, and storing computer executable instructions therein for performing the steps of each method of an embodiment of the present invention when executed by the processor.

[0053] The central processing unit / microprocessor / main control chip 4 may include but is not limited to one or more processors or microprocessors.

[0054] The storage medium 5 may include, but is not limited to, for example, random access memory (RAM), read-only memory (ROM), flash memory, EPROM memory, EEPROM memory, registers, computer storage media (such as hard disk, floppy disk, solid-state drive, removable disk, CD-ROM, DVD-ROM, Blu-ray disc, etc.).

[0055] In addition, the electronic device may also include (but not limited to) a data bus 6, an input / output bus / external bus / device bus 7, a display 8, and input / output devices 9 (eg, keyboard, mouse, speaker, etc.).

[0056] The central processing unit / microprocessor / main control chip etc. 4 can communicate with external devices ( 8 , 9 etc.) via an I / O bus 7 via a wired or wireless network (not shown).

[0057] The storage medium 5 may also store at least one computer executable instruction for executing the various functions and / or method steps in the embodiments described in this technology when run by the central processing unit / microprocessor / main control chip 4.

[0058] In one embodiment, the at least one computer executable instruction may also be compiled into or constitute a software product, wherein one or more computer executable instructions are executed by a processor to perform the various functions and / or method steps in the embodiments described in the present technology.

[0059] Figure 9 A schematic diagram of a computer-readable storage medium according to an embodiment of the present invention is shown.

[0060] like Figure 9 As shown, a non-transitory computer-readable storage medium 11 stores instructions, such as computer-readable instructions 10. When the computer-readable instructions 10 are executed by a processor, the various methods described above can be executed. Non-transitory computer-readable storage media include, but are not limited to, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory (cache), etc. Non-transitory non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. For example, the non-transitory computer-readable storage medium 11 can be connected to a computing device such as a computer, and then, when the computing device executes the computer-readable instructions 10 stored on the computer-readable storage medium 11, the various methods described above can be performed.

[0061] In the several embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interface, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0062] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0063] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0064] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for executing all or part of the steps of the various embodiments of the method of the present invention via a computer device (which can be a personal computer, server, or network device, etc.). The aforementioned storage medium includes various media that can store program code, such as USB flash drives, mobile hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0065] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A vehicle-mounted self-balancing control method, characterized in that: The following steps are involved: Gyroscopes and sensors are placed at key locations on the endoscopic examination table. The gyroscopes are used to capture the table's tilt and rotation data, while the sensors are used to capture the table's vibration and external environmental data, including bumps and vibrations during travel. After receiving data from the gyroscope and sensors, the controller fuses the data through a fusion control algorithm, distinguishes the actual posture changes of the endoscope bed from the external environment data, and calculates the angle and amplitude of the bed that needs to be adjusted; According to the adjustment instructions corresponding to the calculated angle and amplitude, the electric push rod or hydraulic cylinder of the actuator performs the action to adjust the bed posture; If an executing component fails, it automatically switches to the backup component or mode.

2. The vehicle-mounted self-balancing control method according to claim 1, wherein: The process of deploying gyroscopes and sensors at key locations on the endoscopy table includes the following steps: Conduct mechanical analysis on key parts of the bed to determine which areas are affected by the external environment and which areas are sensitive to adjustments to the bed's posture. Key parts include the bed's center of gravity, the connection points of the support frame, and the contact surfaces of the moving devices. The gyroscope is aligned with the rotation axis of the bed, and the sensor is placed in an area that is subject to interference from the external environment; After the deployment is complete, the gyroscope and sensors are connected to the controller and initialized.

3. The vehicle-mounted self-balancing control method according to claim 2, wherein: The calculation formula for bed force distribution in mechanical analysis and key position positioning is: ； Where, It represents the total force on the bed; Indicates the The elastic potential energy of key parts; Indicates the coordinates of the bed in three-dimensional space; Indicates the slight displacement of the bed in three directions; Indicates the The torque of the external environment on the bed; Indicates the The rotation angle under the action of torque; Indicates the number of key parts; Indicates the amount of external environmental interference; Key parts sensitivity assessment formula: ； Where, Indicates the Sensitivity index of key parts; Indicates the The position vector of each key part; Indicates the The posture vectors of key parts; Represents a time variable.

4. The vehicle-mounted self-balancing control method according to claim 3, wherein: The formula for calculating the gyroscope alignment error in the precise placement of the gyroscope and sensor is: ； Where, represents the gyroscope alignment error; Indicates the actual rotation angular velocity measured by the gyroscope; Indicates the angular velocity of the gyroscope under ideal alignment; Sensor placement optimization function: ； Where, represents the optimization objective function of sensor placement, Indicates the The data collection accuracy of each sensor; Indicates the The vibration intensity of the external environment interference; Represents the weight coefficient of the three-dimensional coordinates of space; represents the weight coefficient of the time variable; Indicates the number of sensors; Indicates the amount of external environmental interference.

5. The vehicle-mounted self-balancing control method according to claim 4, wherein: The sensor is connected to the controller, and the adjustment of the initialization error includes: ； Where, Indicates the data acquisition system initialization error; Indicates the Calibration parameters of each sensor; Indicates the The response parameters of each controller; Indicates a time interval; Indicates the frequency interval; Indicates the number of sensors; Indicates the number of controllers; Data transmission delay compensation: ； Where, Indicates the data transmission delay compensation time; Indicates the Transmission delay of each data link; Indicates the Processing delay of each controller; Indicates small changes in data transmission distance; Indicates small changes in the controller's processing power; Indicates the number of data links; Indicates the number of controllers.

6. The vehicle-mounted self-balancing control method according to claim 1, wherein: The process of calculating the angle and amplitude of bed adjustment requires the following steps: Get multi-dimensional data from gyroscopes and sensors; The controller uses dynamic weighting to compare and correct the bed tilt and rotation data captured by the gyroscope with the vibration and external environment data captured by the sensor, organically integrating data from different sources and distinguishing the actual posture changes of the endoscopy bed from the external environment data. The controller calculates the angle and amplitude of the bed that needs to be adjusted based on the organically integrated data; the controller dynamically generates adjustment instructions based on the difference between the current posture of the bed and the target posture, and the adjustment instructions include the current state of the bed.

7. The vehicle-mounted self-balancing control method according to claim 6, wherein: The process of distinguishing the actual posture changes of the endoscopy bed from the external environment data includes the following steps: The controller first obtains multi-dimensional data from the gyroscope and sensors, including bed tilt, rotation, vibration, and external environmental data. It then organically fuses the gyroscope and sensor data using a dynamic weighting formula, using a Gaussian function to eliminate noise and outliers to generate preliminary fused data. Based on the fused data, the controller uses the environmental impact separation formula to eliminate the influence of external environmental data on the bed posture; and uses the change rate of external environmental data and the normalization function to calculate the true posture data; The controller calculates the noise correction factor through the environmental noise correction formula, and performs final correction on the real posture data to generate the bed posture data.

8. The vehicle-mounted self-balancing control method according to claim 6, wherein: The process of dynamically generating adjustment instructions includes the following steps: Perform dynamic calculation based on the difference between the current posture of the bed and the target posture; The controller simulates the movement trajectory of the bed under different adjustment ranges and predicts the adjustment angle and range based on the changing trend of the external environment; Dynamically generate a comprehensive instruction that includes the current state and predicted impact, including the specific angle and amplitude of the bed that needs to be adjusted, as well as a compensation strategy for external environmental interference. If vibration interference is detected in the external environment, the corresponding compensation value is added to the adjustment instruction.

9. The vehicle-mounted self-balancing control method according to claim 1, wherein: The process of executing an action through an electric push rod or hydraulic cylinder of an actuator includes the following steps: The adjustment instructions are transmitted to the electric push rod or hydraulic cylinder. The electric push rod is driven by a precise motor to push or pull the specific part of the bed, while the hydraulic cylinder realizes the smooth adjustment of the bed through the pressure change of the hydraulic system. During the adjustment process, the gyroscope and sensors continuously monitor the changes in the bed's posture and feed back real-time data to the controller; the controller dynamically corrects the adjustment instructions based on the feedback data; If the actuator fails, it automatically switches to the backup component or mode; when the electric push rod fails, the hydraulic cylinder will immediately take over the adjustment task.

10. A vehicle-mounted self-balancing control system, applied to the vehicle-mounted self-balancing control method according to any one of claims 1 to 9, characterized in that: Include: The data acquisition module is configured to deploy gyroscopes and sensors at key locations on the endoscopic examination table. The gyroscope is used to capture the table's tilt and rotation data, and the sensors are used to capture the table's vibration and external environment data, including data on bumps and vibrations during travel. The data calculation module is configured as a controller that receives data from the gyroscope and sensors, fuses the data through a fusion control algorithm, distinguishes the actual posture changes of the endoscope bed from the external environment data, and calculates the angle and amplitude of the bed that needs to be adjusted; The adjustment execution module is configured to perform an action through the electric push rod or hydraulic cylinder of the execution component according to the adjustment instruction corresponding to the calculated angle and amplitude, thereby adjusting the bed posture; If an executing component fails, it automatically switches to the backup component or mode.

Images